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build a Naive Bayes Classifier from scratch for the task of classifying if an email is spam or not.
1. Read section 1 in NLTK chapter 6 and familiarize with the document classification example for movie reviews dataset. 2. Download the dataset from ACL Wiki http://www.aueb.gr/users/ion/data/lingspam_public.tar.gz There are many Spam datasets. Untar the dataset. Google untar and find out how you will deal with a non-zip type archives. 3. Carefully read the readme file. 1. How many folders are there in the archive? 2. What is the difference between the different folders? 4. We will work with Part 1 folder in the lemm_stop folder. Show the code snippet to get marks for this question. 1. How many documents are marked as spam and not spam? How did you come up with the number? 2. How many words are there in all the documents? 3. What are the top 5 frequent words in the spam documents? 4. What are the top 5 frequent words in the non-spam documents? 5. What is the maximum number of words in a document? 6. What is the minimum number of words in a document? 5. Create a feature extractor function similar to document_features in the NLTK example. Don’t copy the code from NLTK book. Use the feature extractor function to create a training dataset on Part 1 of the data. Tra...
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Write 7 pages on what is dyslexia. Include symptoms and causes and diagnosis and treatment in both children and adults.

Write 7 pages on what is dyslexia.

Include symptoms and causes and diagnosis and treatment in both children and adults.

What do parents and teachers do for the child?

My dyslexia paper In APA format.

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